Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

Rendering Falling Leaves on Graphics Hardware

There is a growing interest in simulating natural phenomena in computer graphics applications. Animating natural scenes in real time is one of the most challenging problems due to the inherent complexity of their structure, formed by millions of geometric entities, and the interactions that happen within. An example of natural scenario that is needed for games or simulation programs are forests. Forests are difficult to render because the huge amount of geometric entities and the large amount of detail to be represented. Moreover, the interactions between the objects (grass, leaves) and external forces such as wind are complex to model. In this paper we concentrate in the rendering of falling leaves at low cost. We present a technique that exploits graphics hardware in order to render thousands of leaves with different falling paths in real time and low memory requirements.

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Raster grids detailing the benthic environment of South Georgia

This dataset contains raster grids in GeoTIFF format describing the benthic environment of South Georgia. The data include topographic layers that are directly calculated from a bathymetry grid (Slope, Aspect, Roughness, Slope, Terrain Ruggedness Index, Topographic Position Index). A benthic classification of the area is included, based on topographic layers. Also included are sea-bed environmental layers that are interpolated from global three dimensional grids (Alkalinity, Apparent Oxygen Utilisation, Omega Aragonite, Omega Calcite, Dissolved Oxygen, Nitrate, pH, Phosphate, Salinity, Silicate, Temperature, and Total CO2). These layers were used to construct a habitat suitability model for Octocorallia. The geographic extent is 43°57'56.65"W - 33°45'38.19"W and 52°47'29.50"S - 56° 9'11.03"S. The spatial resolution is 150m x 150m (except for benthic classification wihch is 450m x 450m). The map projection is EPSG:3762.

Global raster maps indicating the habitat suitability for 7 suborders of cold water octocorals (Octocorallia found deeper than 50m)

This dataset consists of global raster maps indicating the habitat suitability for 7 suborders of cold water octocorals (Octocorallia found deeper than 50m). Maps present a relative habitat suitability index ranging from 0 (unsuitable) to 100 (highly suitable). Two maps are provided for each suborder (Alcyoniina, Calcaxonia, Holaxonia, Scleraxonia, Sessiliflorae, Stolonifera, and Subselliflorae). A publicly accessable low resolution map (grid size 10x10 arc-minutes) and a restricted access high resolution map (grid size 30x30 arc-seconds). Maps are geotiff format incorporating LZW compression to reduce file size. Please contact the corresponding author (Chris Yesson) for access to the high resolution data.

Raster maps for 29 environmental variables in three geographical regions

Aim: Greater understanding of the processes underlying biological invasions is required to determine and predict invasion risk. Two subspecies of olive (Olea europaea subsp. europaea and Olea europaea subsp. cuspidata) have been introduced into Australia from the Mediterranean Basin and southern Africa during the 19th century. Our aim was to determine to what extent the native environmental niches of these two olive subspecies explain the current spatial segregation of the subspecies in their non-native range. We also assessed whether niche shifts had occurred in the non-native range, and examined whether invasion was associated with increased or decreased occupancy of niche space in the non-native range relative to the native range. Location: South-eastern Australia, Mediterranean Basin and southern Africa. Methods: Ecological niche models (ENMs) were used to quantify the similarity of native and non-native realized niches. Niche shifts were characterized by the relative contribution of niche expansion, stability and contraction based on the relative occupancy of environmental space by the native and non-native populations. Results: Native ENMs indicated that the spatial segregation of the two subspecies in their non-native range was partly determined by differences in their native niches. However, we found that environmentally suitable niches were less occupied in the non-native range relative to the native range, indicating that niche shifts had occurred through a contraction of the native niches after invasion, for both subspecies. Main conclusions: The mapping of environmental factors associated with niche expansion, stability or contraction allowed us to identify areas of greater invasion risk. This study provides an example of successful invasions that are associated with niche shifts, illustrating that introduced plant species are sometimes readily able to establish in novel environments. In these situations the assumption of niche stasis during invasion, which is implicitly assumed by ENMs, may be unreasonable.

Raster grids detailing habitat suitability for Lophelia pertusa reefs in the Irish continental margin

This dataset contains raster grids in GeoTIFF format describing the habitat suitability for living Lophelia pertusa reefs in the Irish continental margin (extended continental shelf claim). The habitat suitability map is given in continuous and binary (based on the 10th percentile threshold) format. The geographic extent is 25°53.801'W - 6°42.401'W and 46°45.033'N - 57°27.033'N. The spatial resolution is 0.01°x0.01°. The map projection is WGS 1984.

Datos geográficos de tipo raster en R

El paquete raster proporciona un gran número de funciones para procesar datos geográficos de tipo raster. El diseño de este paquete, basado en clases S4, hace el análisis de estos datos más amigable al usuario. También ha ocasionado el desarrollo de paquetes más específicos para trabajar con datos raster en R. rasterVis proporciona un conjunto de métodos de visualización e interacción gráfica, desde gráficos de nivel y contorno, histogramas o matrices de dispersión, hasta gráficos apropiados para datos espacio-temporales. gdistance proporciona nuevas clases para cálculos basados en rutas y movimientos a través de espacios discretizados. Implementa métodos como la distancia de coste e introduce métodos recientemente desarrollados basados en caminos aleatorios. En la charla se explicará el diseño del paquete raster y se demostrará las posibilidades que ofrecen estos paquetes con ejemplos concretos

Area-delay Trade-offs of Texture Decompressors for a Graphics Processing Unit

Graphics Processing Units have become a booster for the microelectronics industry. However, due to intellectual property issues, there is a serious lack of information on implementation details of the hardware architecture that is behind GPUs. For instance, the way texture is handled and decompressed in a GPU to reduce bandwidth usage has never been dealt with in depth from a hardware point of view. This work addresses a comparative study on the hardware implementation of different texture decompression algorithms for both conventional (PCs and video game consoles) and mobile platforms. Circuit synthesis is performed targeting both a reconfigurable hardware platform and a 90nm standard cell library. Area-delay trade-offs have been extensively analyzed, which allows us to compare the complexity of decompressors and thus determine suitability of algorithms for systems with limited hardware resources.

Combining Text and Graphics for Interactive Exploration of Behavior Datasets

Modern sensor technologies and simulators applied to large and complex dynamic systems (such as road traffic networks, sets of river channels, etc.) produce large amounts of behavior data that are difficult for users to interpret and analyze. Software tools that generate presentations combining text and graphics can help users understand this data. In this paper we describe the results of our research on automatic multimedia presentation generation (including text, graphics, maps, images, etc.) for interactive exploration of behavior datasets. We designed a novel user interface that combines automatically generated text and graphical resources. We describe the general knowledge-based design of our presentation generation tool. We also present applications that we developed to validate the method, and a comparison with related work.

Novel educational assessment for building structures: Automatic evaluation of on-line graphics

This article presents a new automatic evaluation for on-line graphics, its application and the numerous advantages achieved applying this developed correcting method. The software application developed by the Innovation in Education Group “E4”, from the Technical University of Madrid, is oriented for the online self-assessment of the graphic drawings that students carry out as continuous training. The adaptation to the European Higher Educational Area is an important opportunity to research about the possibilities of on-line education assessment. In this way, a new software tool has been developed for continuous self-testing by undergraduates. Using this software it is possible to evaluate the graphical answer of the students. Thus, the drawings made on-line by students are automatically corrected according to the geometry (straight lines, sloping lines or second order curves) and by sizes (depending on the specific values which define the graphics).